Founding AI Engineer

About Clark

Clark, previously known as uiAgent, is an innovative AI platform created to assist audit teams during active engagements. The platform's AI agent, Ava, automates substantial audit fieldwork tasks such as population testing, verification, recalculation, and preparation of working papers, while ensuring firm partners maintain control over critical judgments and client relationships. Clark blends AI capabilities with human oversight to deliver faster, superior-quality audits, allowing CPAs to focus more on strategic and analytical responsibilities.

Role Overview

As a founding member of the AI engineering team at Clark, you will be responsible for designing, developing, and deploying the key AI components powering Ava. This full-time, on-site position based in Heidelberg involves collaboration with product managers, engineering teams, and domain experts to build machine learning models, create NLP functionalities, and implement cutting-edge neural network solutions within production software.

Responsibilities

• Prototype and assess innovative AI methodologies.
• Develop and maintain robust data pipelines supporting model performance.
• Enhance model capabilities and ensure scalability and reliability of deployed systems.
• Contribute broadly across the engineering technology stack.
• Participate actively in code reviews and establish best technical practices.
• Influence the company’s technical roadmap and foster a strong engineering culture.
• Mentor new engineering hires as the team expands.

Qualifications

• Solid grounding in computer science concepts such as algorithms, data structures, and software engineering.
• Experience in neural networks and pattern recognition including design, training, and evaluation of machine learning architectures.
• Proficiency in software development with Python or similar languages applicable to production ML systems.
• Practical knowledge of natural language processing techniques like language modeling, text classification, or information extraction.
• Bachelor’s or higher academic degree in computer science, engineering or related fields, or equivalent hands-on experience.
• Hands-on experience deploying machine learning models into production, involving cloud infrastructure, containerization, and CI/CD pipelines.
• Strong analytical problem-solving ability; comfortable in a dynamic startup environment and working collaboratively across teams.
• Experience or understanding of financial services, audit, or accounting workflows is advantageous, along with backgrounds in fast-growing tech firms.